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Feb 24, 2021

POAI ‘s Helomics Division Announces Progress on Milestones for its AI-Driven Model of Ovarian Cancer

Helomics Researchers Complete Key Sequencing Milestones and Focus on AI-Driven Model Building

MINNEAPOLIS, Feb. 24, 2021 (GLOBE NEWSWIRE) -- Predictive Oncology (NASDAQ: POAI), a knowledge-driven company focused on applying artificial intelligence (“AI”) to personalized medicine and drug discovery, is excited to announce today that it has completed key data generation milestones in its retrospective study in collaboration with UPMC-Magee Women Hospital, to build AI-driven models of ovarian cancer. Comprehensive genomic and transcriptomic sequencing of patient samples is now complete and patient outcome data has been obtained from UPMC-Magee. These data will now be used to drive both our AI-models of ovarian cancer as well as our internal ovarian cancer drug re-purposing project.

“We are excited to have reached these key sequencing and data generation milestones as these data are the foundation of our AI-driven predictive models of patient outcome, which will further extend our clinical offering and help oncologists individualize patient therapy. In addition, these data will play an important role in our internal drug repurposing project for ovarian cancer, by providing additional information to help drive our AI-driven patient-centric platform, PeDAL™," explained Dr Schwartz, CEO of POAI.

“The successful generation of high quality genomic and transcriptomic data from archived materials at Helomics, together with the gathering of historical outcome data from our collaborator UPMC-Magee, demonstrates that we can leverage Helomics’ unique asset and deliver significant value. Furthermore, this project is a template we can use to partner with other healthcare institutions and expand our AI-driven clinical models to other cancers,” added Dr. Schwartz.

About Predictive Oncology Inc.

Predictive Oncology (NASDAQ: POAI) operates through three segments (Skyline, Helomics and Soluble Biotech), which contain four subsidiaries: Helomics, TumorGenesis, Skyline Medical and Soluble Biotech.

Helomics applies artificial intelligence to its rich data gathered from patient tumors to both personalize cancer therapies for patients and drive the development of new targeted therapies in collaborations with pharmaceutical companies. TumorGenesis Inc. specializes in media that help cancer cells grow and retain their DNA/RNA and proteomic signatures, providing researchers with a tool to expand and study cancer cell types found in tumors of the blood and organ systems of all mammals, including humans. Skyline Medical markets its patented and FDA cleared STREAMWAY System, which automates the collection, measurement and disposal of waste fluid, including blood, irrigation fluid and others, within a medical facility, through both domestic and international divisions. Soluble Biotech is a provider of soluble and stable formulations for proteins including vaccines, antibodies, large and small proteins and protein complexes. For more information, please visit www.predictive-oncology.com.

Forward-looking Statements

Certain of the matters discussed in this press release contain forward-looking statements that involve material risks to and uncertainties in the Company’s business that may cause actual results to differ materially from those anticipated by the statements made herein. Such risks and uncertainties include: market and other conditions, the completion of the private placement, the satisfaction of customary closing conditions related to the private placement and the intended use of net proceeds from the private placement, a variety of other risks and uncertainties including, among other things, factors discussed under the heading “Risk Factors” in our filings with the SEC. Except as expressly required by law, the Company disclaims any intent or obligation to update these forward-looking statements.

Investor Relations Contact:

Landon Capital
Keith Pinder
(404) 995-6671
kpinder@landoncapital.net


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Source: Predictive Oncology Inc.